CloudMan and Galaxy API library
Project description
BioBlend is a Python (2.6 or 2.7) library for interacting with CloudMan and Galaxy’s API.
Conceptually, it makes it possible to script and automate the process of cloud infrastructure provisioning and scaling via CloudMan, and running of analyses via Galaxy. In reality, it makes it possible to do things like this:
Create a CloudMan compute cluster, via an API and directly from your local machine:
from bioblend.cloudman import CloudManConfig from bioblend.cloudman import CloudManInstance cfg = CloudManConfig('<your cloud access key>', '<your cloud secret key>', 'My CloudMan', 'ami-<ID>', 'm1.small', '<password>') cmi = CloudManInstance.launch_instance(cfg) cmi.get_status()Reconnect to an existing CloudMan instance and manipulate it:
from bioblend.cloudman import CloudManInstance cmi = CloudManInstance("<instance IP>", "<password>") cmi.add_nodes(3) cluster_status = cmi.get_status() cmi.remove_nodes(2)Interact with Galaxy via a straightforward API:
from bioblend.galaxy import GalaxyInstance gi = GalaxyInstance('<Galaxy IP>', key='your API key') libs = gi.libraries.get_libraries() gi.workflows.show_workflow('workflow ID') gi.workflows.run_workflow('workflow ID', input_dataset_map)Interact with Galaxy via an object-oriented API:
from bioblend.galaxy.objects import GalaxyInstance gi = GalaxyInstance("URL", "API_KEY") wf = gi.workflows.list()[0] hist = gi.histories.list()[0] inputs = hist.get_datasets()[:2] input_map = dict(zip(wf.input_labels, inputs)) params = {"Paste1": {"delimiter": "U"}} wf.run(input_map, "wf_output", params=params)
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